Github user ajtulloch commented on the pull request:
https://github.com/apache/spark/pull/458#issuecomment-42758859
I agree with @etrain, it's possible to abstract out the ADMM optimisation
routine such that it's trivial to implement L1-logistic regression, lasso,
[SVMs](http://web.eecs.umich.edu/~honglak/aistats12-admmDistributedSVM.pdf),
etc with very few additional lines of code. I implemented that for Spark a few
months ago (albeit a naive, unperformant, and untested implementation).
If you wanted to see an alternative way of structuring this diff, my code
is available at
[ajtulloch/spark/SPARK-1794-GenericADMM](https://github.com/ajtulloch/spark/tree/SPARK-1794-GenericADMM).
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